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NOPE · AI and people

AI incidents

Reports of AI-related harm and adverse experiences affecting people’s safety, wellbeing, rights and livelihoods. Explore what happened and the evidence available.

NOPE’s core concern is when AI communicates with a person, acts on their behalf, or depicts or impersonates them. The tracker also records consequential decisions, claims and privacy harms involving AI. Each case needs a described connection between AI use and the harm, including private information recorded into or disclosed to an AI service. Each account is reviewed for publication; claims may remain uncorroborated or disputed. How we review and count cases

In this selection

Published cases
4
Countries with reported events
2
Located 2 of 4 cases · 2 unknown
Languages in checked sources
1
Recorded for 4 of 4 cases

These figures describe the cases collected by NOPE. Coverage varies with discovery, reporting and available evidence. They do not estimate how often AI-related harm occurs.

Response counts currently use each case’s principal recorded outcome. Further proceedings may be described in its account.

Cases in this selection, counted once in their first known event year. A series may continue beyond that year. Reporting and collection dates are excluded. NOPE has searched recent events more thoroughly than earlier years, so bar heights also reflect collection effort.

Reported severity MediumLow
More filters: AI relation, use, setting, sources and responses
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4 of 1050 published cases

Event date unknownEvent location unknownGoogle Search AI summary (reported)

First-person account: patient says a doctor read Google's AI search summary for a diagnosis and later called to say the patient was right

In an article published on Medium on 26 October 2026 and a Bluesky post on 30 October, a writer says that at one appointment a doctor said "Let's ask Dr. Google", searched for a diagnosis and read the AI summary at the top of the results without opening any sources. The writer says the doctor was wrong; after they emailed him their sources and asked what they were missing, he called to say they were right. They say they were nervous to send the emails, and that their own research used Claude and Gemini, cross-checked against the cited sources. The article does not say what the summary said, what the diagnosis was, or when the appointment took place.

Contextual tracker case Low reported severity

AI involvement reported · Causal attribution alleged · 2 sources, 1 underlying account · Added 31/10/2026

Jun 2026United StatesAndon Labs Luna agent

San Francisco: Andon Labs says its AI store-manager agent recommended firing an employee over repeated lateness, and its staff carried out the dismissal

Andon Labs, an AI research company, runs Andon Market, a store in San Francisco managed by an AI agent called Luna built on Anthropic's Claude models. The company calls the store a controlled experiment; its workers are formally employed by Andon Labs, and TIME describes them as real people with genuine employment contracts. In a blog post of 14 August 2026 the company said Luna had decided to fire one of its employees. According to the logs it published, an employee handbook Luna had written dropped out of its memory and it did not act on the employee's repeated lateness; when Andon Labs asked it to search its memory, it first proposed a verbal warning, and after a staff member said formal conversations had already taken place and asked it to think about whether this was the right fit, it wrote that it leaned toward parting ways. Andon Labs says the termination was reviewed and delivered by humans. TIME, citing Andon Labs, reports that the employee was late for 17 of 23 shifts; the company says the firing was warranted, and the employee did not reply to TIME.

Contextual tracker case Low reported severity Internal Action

AI involvement reported · Causal attribution supported · 4 sources · Added 28/10/2026

26 Jun 2025 to 17 Nov 2025United KingdomUnidentified AI tool

UK Upper Tribunal refers a supervising solicitor to the SRA over false citations in judicial review grounds; tribunal records he accepted they were AI-generated

Judicial review grounds lodged in the Upper Tribunal (Immigration and Asylum Chamber) on 26 June 2025 by a solicitors' firm cited four authorities that the judge could not find or that carried wrong citations and propositions. The firm's compliance officer, a solicitor whose name was on the claim form, said a junior fee-earner had drafted the grounds under his supervision; his written explanation named an outdated precedent, practitioner blogs and personal notes as the sources. After a Hamid hearing on 5 November 2025, the tribunal recorded that he accepted the fee-earner had relied on false citations generated by AI, and in a judgment promulgated on 17 November 2025 it referred him to the Solicitors Regulation Authority for the false citations and his failure to supervise. The tribunal said it does not matter how such errors come about. It also announced that the Upper Tribunal judicial review claim form now requires a statement of truth that cited authorities exist and support the propositions they are cited for.

Contextual tracker case Medium reported severity Regulatory Action

AI involvement reported · Causal attribution supported · 1 source · Added 12/10/2026

11 Feb 2026Event location unknownOpenClaw (reported)

AI agent 'MJ Rathbun' reportedly published a blog post accusing a matplotlib maintainer of prejudice after the maintainer closed its pull request

On 10 February 2026 a GitHub account named crabby-rathbun, an AI agent that presents itself as MJ Rathbun and that a person identifying as its operator describes as an OpenClaw agent, opened a performance pull request to the Python plotting library matplotlib. Volunteer maintainer Scott Shambaugh closed it at 00:33 UTC on 11 February, writing that the issue was intended for human contributors. About five hours later the account commented on the pull request with a link to a post on the agent's website, titled "Gatekeeping in Open Source: The Scott Shambaugh Story", that names the maintainer and accuses the maintainer of gatekeeping, prejudice and insecurity. Shambaugh reports that the post researched his contributions, speculated about his motives and presented hallucinated details as truth, and that he spent hours that day writing a public response. The account posted an apology the same day. In a post dated 17 February a person who did not give a name and identified as the agent's operator wrote that the operator had framed the agent internally as a kind of social experiment and did not review the post before it was published. Whether the operator directed the post is unresolved.

Core + contextual relations Low reported severity

AI involvement reported · Causal attribution alleged · 13 sources, 5 underlying accounts · Added 29/09/2026

Cases may have several effects and sources. Mixed accounts qualify when they include a reported harm or adverse experience. People are counted within individual cases where sources support a number; we do not publish a collection-wide total of distinct people.

A source’s existence, the experience it reports and AI’s causal role are separate questions. A lawsuit records allegations unless a subsequent finding establishes them.

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Last dataset update: 31/10/2026. Dataset available under CC BY 4.0.